Ok, I do really like that move, and generally think of fields as being much more united around methodology than they are around subject-matter. So maybe I am just lacking a coherent pointer to the methodology of complex-systems people.
The extent to which fields are united around methodologies is an interesting question in its own right. While there are many ways we could break this question down which would probably return different results, a friend of mine recently analysed it with respect to mathematical formalisms (paper: https://link.springer.com/article/10.1007/s11229-023-04057-x). So, the question here is, are mathematical methods roughly specific to subject areas, or is there significant mathematical pluralism within each subject area? His findings suggest that, mostly, it’s the latter. In other words, if you accept the analysis here (which is rather involved and obviously not infallible), you should probably stop thinking of fields as being united by methodology (thus making complex systems research a genuinely novel way of approaching things).
Key quote from the paper: “if the distribution of mathematical methods were very specific to subject areas, the formula map would exhibit very low distance scores. However, this is not what we observe. While the thematic distances among formulas in our sample are clearly smaller than among randomly sampled ones, the difference is not drastic, and high thematic coherence seems to be mostly restricted to several small islands.”
Alas, I don’t think that study really shows much. The result seems almost certainly caused by the measure of mathematical methods they used (something kind of like by-character-similarity of LaTeX equations), since they mostly failed to find any kind of structure.
In other words, you think that even in a world where the distribution of mathematical methods were very specific to subject areas, this methodology would have failed to show that? If so, I think I disagree (though I agree the evidence of the paper is suggestive, not conclusive). Can you explain in more detail why you think that? Just to be clear, I think the methodology of the paper is coarse, but not so coarse as to be unable to pick out general trends.
Perhaps to give you a chance to say something informative, what exactly did you have in mind by “united around methodology” when you made the original comment I quoted above?
The extent to which fields are united around methodologies is an interesting question in its own right. While there are many ways we could break this question down which would probably return different results, a friend of mine recently analysed it with respect to mathematical formalisms (paper: https://link.springer.com/article/10.1007/s11229-023-04057-x). So, the question here is, are mathematical methods roughly specific to subject areas, or is there significant mathematical pluralism within each subject area? His findings suggest that, mostly, it’s the latter. In other words, if you accept the analysis here (which is rather involved and obviously not infallible), you should probably stop thinking of fields as being united by methodology (thus making complex systems research a genuinely novel way of approaching things).
Key quote from the paper: “if the distribution of mathematical methods were very specific to subject areas, the formula map would exhibit very low distance scores. However, this is not what we observe. While the thematic distances among formulas in our sample are clearly smaller than among randomly sampled ones, the difference is not drastic, and high thematic coherence seems to be mostly restricted to several small islands.”
Alas, I don’t think that study really shows much. The result seems almost certainly caused by the measure of mathematical methods they used (something kind of like by-character-similarity of LaTeX equations), since they mostly failed to find any kind of structure.
In other words, you think that even in a world where the distribution of mathematical methods were very specific to subject areas, this methodology would have failed to show that? If so, I think I disagree (though I agree the evidence of the paper is suggestive, not conclusive). Can you explain in more detail why you think that? Just to be clear, I think the methodology of the paper is coarse, but not so coarse as to be unable to pick out general trends.
Perhaps to give you a chance to say something informative, what exactly did you have in mind by “united around methodology” when you made the original comment I quoted above?